Start param estimation

nasa · Oct 29, 2024 · 9cdafff · 9cdafff
1 parent f5b9238
commit 9cdafff
Showing 1 changed file with 111 additions and 4 deletions.
diff --git a/examples/2024PHMTutorial.ipynb b/examples/2024PHMTutorial.ipynb
@@ -1168,16 +1168,123 @@
     "fig = results.outputs.plot()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Parameter Estimation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "times = dataset['absoluteTime']\n",
+    "inputs = [elem[1]['voltage'] * elem[1]['current'] for elem in dataset.iterrows()]\n",
+    "outputs = [{'v': elem[1]['voltage']} for elem in dataset.iterrows()]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def future_load(t, x=None):\n",
+    "    power = np.interp(t, times, inputs)\n",
+    "    return {'P': power}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = m.simulate_to(30116.56, future_load, dt=1, save_freq=100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "plt.plot(times, [z for z in dataset['voltage']])\n",
+    "plt.plot(results.times, [z['v'] for z in results.outputs])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m.parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m['v_L'] = m['v_L']/4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inputs_reformatted = [{'v': elem[1]['voltage'] * elem[1]['current']} for elem in dataset.iterrows()]\n",
+    "keys = ['v_L', 'lambda', 'gamma', 'mu', 'beta', 'x0']\n",
+    "print('Model configuration before')\n",
+    "for key in keys:\n",
+    "    print(\"-\", key, m[key])\n",
+    "print('Error: ', m.calc_error(times=times.to_list(), inputs=inputs_reformatted, outputs=outputs))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m.estimate_params(times=times.to_list(), inputs=inputs_reformatted, outputs=outputs, dt=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for key in keys:\n",
+    "    print(\"-\", key, m[key])\n",
+    "print('Error: ', m.calc_error(times=times.to_list(), inputs=inputs_reformatted, outputs=outputs))"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "current = [165/z['v'] for z in results.outputs]\n",
-    "import matplotlib.pyplot as plt\n",
-    "fig = plt.plot(current)\n",
-    "fig = results.inputs.plot()"
+    "results.outputs.plot()"
    ]
   },
   {